I am vice president of AI Science here at IBM Research.
Previously, I was a Fellow, vice preident and general manager of research at Infosys.
I have also been CTO, co-founder and then CEO of Skytree, the Machine Learning Company.
About my work:
My work has focused on developing the new statistical and computational principles demanded by next-generation challenges in data analysis and autonomy. I have developed new methods directly driven by, informed by, and validated by hard real problems, often by bridging technical intuitions or mathematical concepts from distant fields and perspectives.
Two key challenges of modern computational science that have kept me awake at night are massive datasets and various curses of dimensionality. I have been concerned with computational strategies for dealing with the fundamental summations, integrals, and maximizations at the root of a wide variety of statistics and machine learning methods. My recent research concerned alternative statistical theory for certain old problems. A long-term target is to nail down enough powerful and general statistical and computational foundational primitives to achieve automatic data analysis and data-driven control, a bottom-up path to fully autonomous systems.
About my education:
After completing bachelor's degrees in applied mathematics (concentration in computational statistics) and computer science from UC Berkeley, and after having spent summers at the Santa Fe Institute and Los Alamos National Laboratory, among other places, I worked for 6 years in the machine learning systems group of NASA's Jet Propulsion Laboratory. I completed my PhD on 4/29/03 in computer science after 3.6 years at Carnegie Mellon University, advised by Prof. Andrew Moore. I have been a postdoctoral fellow in the Robotics Institute, and an assistant professor at Georgia Tech.